Wednesday, April 2, 2008 - 11:30 AM

OPTIRESOURCE: Convincing decision makers by scientific facts and figures

Joerg Wind and Peter Froeschle. Daimler (former: DaimlerChrysler)

Optiresource is a software for the analysis and visualization of car-related energy chains and energy scenarios (in terms of energy consumption, greenhouse gas emissions and fossil fuel content). It is very helpful for the definition of strategies focusing on the global “Well-to-Wheel” analysis. As it is displaying complex scientific results in a easy understandable way, it is suitable to convince decision makers about the benefits of technologies which lead to a reduction of energy consumption and greenhousegas (GHG)-emissions. It provides a quick and clear answer to several questions:

-         What is obtained comparing the different energy chains in terms of energy consumptions, greenhouse gas emissions, etc?

-         What do the energy chains allow in terms of optimization of the consumptions and emissions?

-         What is the impact of different energy scenarios?

-         What/how do energy choices optimize the consumptions and emissions?

-         And many others...

 

 

Due to the large variety of combinations of primary energy, process, fuel and drive train, it is often not easy to find the relevant data sets quickly. In 2004 Daimler therefore decided to realize a tool for an interactive visualization of all existing energy paths. The used data were taken from the Well-to-Wheel report done by EUCAR and CONCAWE in cooperation with the European Joint Research Center. Additional data sets, e.g. from US-American studies can be integrated in the software.

 

The software has two operation modes, the query mode and the scenario mode. In the query mode, the energy chains chosen by the user can easily be compared with respect to well-to-wheel (WTW) energy consumption and WTW GHG-emissions. Furthermore well-to-tank (WTT) and tank-to-wheel (TTW) values can also be displayed as well as the used amount of fossil energy. With this tool, the benefits of hydrogen and fuel cell drive trains can easily be shown to interested decision makers. Additionally, using the scenario mode, the effect of the introduction of alternative drive trains and fuels can be investigated. It is possible to generate any scenario for future vehicle fleet composition. Using this tool, it could be shown that the hydrogen fueled fuel cell vehicle has the largest impact on energy consumption and GHG emissions, other options like biofuels do not have a similar effect. In the presentation as one example a case study comparing  compressed vs. liquefied hydrogen used in a fuel cell vehicle vs. an internal combustion engine will be shown. Conclusions will be shown and explained.